Methods for radio frequency spectral analysis

ABSTRACT

The invention is directed to methods for radio frequency spectral analysis. Accordingly, flight instructions are executed on a first UAV to fly in a first flight pattern relative to a signal source. The first UAV detects radio signal(s) from the signal source and associated signal data. Flight instructions are concurrently executed on a second UAV to fly in a second flight pattern, relative to the first flight pattern of the first UAV. The second UAV also detects radio signal(s) from the signal source and associated signal data. The stored signal data from the drones may then be processed for visualization.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.14/693,065 filed on Apr. 22, 2015, which has matured into U.S. Pat. No.9,847,035 on Dec. 19, 2017, which claims the benefit of U.S. ProvisionalPatent Application No. 62/108,590, filed on Jan. 28, 2015, the contentsof these applications are herein incorporated by reference.

BACKGROUND OF THE INVENTION Field of the Invention

This invention generally relates to systems and methods for performingradio frequency spectral analysis. Specifically, an unmanned aerialvehicle is utilized to measure radio signal(s) in real time, and torelay parameters thereof to a processing device over a network foranalysis and visualization of the radio signal(s). A radio frequencypre-selector may be utilized to preselect a frequency band forperforming the spectral analysis. A plurality of unmanned aerialvehicles may be deployed concurrently in order to obtain an accurate 3Drepresentation.

Description of the Related Art

Spectral analyzers are hardware devices which measure the magnitude ofan input signal versus frequency. The primary use of a spectral analyzeris to measure the power of the spectrum of various signals. By analyzingthe spectral of the various signals, the dominant frequency, band,power, distortion, harmonics, bandwidth, and other spectral componentsof one or more signals can be observed that are not otherwise easilydetectable.

The use of spectral analyzers is often employed to measure radiofrequency, such as the frequency response, noise, and distortioncharacteristics, by comparing the input and output spectra of afrequency generating device. In telecommunications such as cellular andradio towers, spectrum analyzers are also used to determine occupiedbands, and importantly to track interference sources. For example, cellphone carriers and providers use spectrum analyzers to determineinterference sources in GSM and UMTS frequency bands when planning toerect cellular towers or transmitters. In EMC testing, a spectrumanalyzer is used for basic pre-compliance testing in order to assesswhether a wireless transmitter is working in accordance to federallydefined standards for purity of emissions. For instance, output signalsat frequencies other than the intended or licensed frequency spectrumwould be flagged.

However, current methods employed in the measurement of interferencesources and various signal characteristics presents a challenge.Specifically, it would prove difficult to maneuver various radios orreceivers for mapping a three dimensional view of signal characteristicswith real obstacles. Moreover, it may be burdensome or difficult tomaneuver and/or to stabilize RF spectral analyzers in densely populatedor crowded areas, such as buildings surrounding cellular towers orrepeaters. Moreover, any attempt to manually measure signalcharacteristics via, for example, a crane, scissor-lift, cherry-picker,or other industrial equipment, would result in the industrial equipmentitself providing substantial interference due to the size, weight, andamount of metal in the industrial equipment.

Accordingly, there exists a need in the cellular and wirelesscommunication industry for a system and method that can easily maneuverbetween cellular tower antennas, power lines, and relay accurate fieldcharacteristics and particularly an aerial vehicle based system andmethod.

SUMMARY OF THE INVENTION

The present invention is generally directed to a system and methods forperforming radio frequency spectral analysis. Specifically, the presentinvention utilizes an unmanned aerial vehicle (UAV) in combination witha spectral analyzer for measuring signal levels from radio frequency(RF) emitting devices, and relay them to a ground station in real timeor near real time using either direct radio broadcasts, LTE protocol, orother cellular communication channels, in order to provide a live viewof three dimensional field characteristics for visualization by a user.Additionally, the size and weight of a UAV generate little, if any,interference, especially where the UAV selected is less than about 1meter in diameter and/or weighs less than about 55 pounds.

Accordingly, a system of the present invention generally comprises a UAVand a processing device. The UAV is structured for flight and configuredto detect radio signal(s) produced by a signal source, and store variousparameters of the radio signal(s) as signal data for processing and/orvisualization. The UAV may store the signal data in onboard memory, ormay be configured to transmit the signal data over a network to aprocessing device. The processing device may comprise an applicationserver having a database, which may process the signal data and displaythe information to at least one user, or multiple users concurrently. Assuch, the processing device may further be accessible or viewable from aremote device, such as a networked computer or mobile device.

The UAV may comprise a flight body, processor, memory, flight module, ageolocation module, a signal detection module, and a communicationsmodule. The flight body may comprise rotary drones or fixed wing dronesand appropriate components thereof, such as a hull, a power source,wings and/or at least one actuated propeller. The processor and memoryare structured and configured to allow the various modules to functionand communicate with one another, and to direct flight controls tocomponents of the flight body.

The flight module is configured to receive programmed flightinstructions, either pre-programmed or via wireless communications froma ground station, processing device over a network, or remote control,in order to facilitate the unmanned flight of the UAV. The geolocationmodule is configured to determine the UAV's present location, and maycomprise a GPS, altimeter, accelerometer, and other appropriatecomponents.

The signal detection module is configured to detect radio signal(s)within range of the UAV and store and/or transmit the signal dataassociated with the radio signal(s). Signal detection module may furthercomprise a software defined radio and a radio frequency spectrumpre-selector. The communications module is configured to transmit thesignal data from the signal detection module, as well as geolocationdata from the geolocation module, over a network or directly to aprocessing device.

Because the onboard UAV signal detection module and communicationsmodule are rather limited, due to weight and space constraints, it istherefore desirable to limit detected radio frequencies in order toreduce overhead, power consumption, and save data transmissionbandwidth. Therefore, additional embodiments of the present inventionare directed to systems and methods for pre-selecting a frequency bandfor radio frequency spectral analysis.

Accordingly, a system for pre-selecting a frequency band for radiofrequency spectral analysis may comprise a signal receiver, a radiofrequency pre-selector, an optional second receiver, a software definedradio, and a switch controller.

The signal receiver is structured to receive radio signal(s) as an inputsignal. The radio frequency pre-selector comprises a signal inputmodule, pre-selector switch, a plurality of filter modules, and a signaloutput module. Signal input module may comprise at least an inputamplifier to boost the gain of the incoming signals. The pre-selectorswitch connects the signal input module or alternatively, the signalreceiver directly, to the plurality of filter modules. The pre-selectorswitch may be controllable directly by a user through a process deviceor remote device, or in other embodiments be automatically controllableby a controller.

Each of the plurality of filter modules correspond with a predeterminedfrequency band in the radio frequency spectrum or other user definedspectrum. Each filter module may comprise at least one filter forpassing through desired signal frequencies or a frequency band, whilefiltering out other frequencies. The output signal module may compriseadditional amplifiers and other signal processing circuitry to boost thegain of the desired signal while reducing noise and interference.Shielding may be used on the radio frequency pre-selector or othercomponents described herein to further reduce interference.

The software defined radio (SDR) is structured and configured to detectand receive radio signal(s). In one embodiment, the SDR utilizes theoptional second receiver, separate from the receiver connected to theradio frequency pre-selector for listening to or receiving radiosignal(s). This allows the SDR to function without interfering with theradio frequency pre-selector. In at least one embodiment, the SDR may,through a switch controller, automatically switch the radio frequencypre-selector to a desired filter module corresponding to a band of adetected signal.

Other embodiments of the present invention are directed to coordinatingand/or synchronizing a plurality of UAVs to detect and store radiosignal(s) surrounding a signal source simultaneously, in order toprovide for a visualization of the three dimensional space and fieldcharacteristics of the signal(s) emanating from the signal source.Specifically, a plurality of UAVs, including at least a first and secondUAV, are navigated to a start position. A predefined flight pattern isthen executed on each of the first and second UAVs. The second UAV'sflight pattern may be dynamically calculated and/or determined based onthe first UAV's flight pattern. For example, if the first UAV's flightpattern is set to circumnavigate the signal source at a distance of 3feet, the second UAV's flight pattern may be programmed to dynamicallycircumnavigate the signal source at a distance of two times the setdistance of the first UAV, or 6 feet. Additional UAVs may be added tosimultaneously detect and store received signal data surrounding asignal source or proximate to a signal source. The recorded signal datafrom the plurality of UAVs are then used to create a visualization ofspace surrounding or proximate to the signal source, and may comprise aSmith Chart or other diagrammatic representation of signal frequencyand/or amplitude at various points in Cartesian space.

These and other objects, features and advantages of the presentinvention will become clearer when the drawings as well as the detaileddescription are taken into consideration.

BRIEF DESCRIPTION OF THE DRAWINGS

For a fuller understanding of the nature of the present invention,reference should be had to the following detailed description taken inconnection with the accompanying drawings in which:

FIG. 1 is a diagrammatic representation illustrating a system for radiofrequency spectral analysis.

FIG. 2 is schematic representation illustration an unmanned aerialvehicle for radio frequency spectral analysis.

FIG. 3 is a flowchart of a method for radio frequency spectral analysis,where the signal data is transmitted and processed over a network.

FIG. 4 is a flowchart of another method for radio frequency spectralanalysis, where the unmanned aerial vehicle is programmed to search forpredetermined parameters in radio signal(s).

FIG. 5 is a flowchart of another method for radio frequency spectralanalysis, where the unmanned aerial vehicle is programmed to follow andmap the radio signal(s).

FIG. 6 is a diagrammatic representation illustrating the functionalityof a radio frequency pre-selector.

FIG. 7 is a schematic representation illustrating a system forpre-selecting a frequency band for radio frequency spectral analysis.

FIG. 8 is a flow chart of a method for pre-selecting a frequency bandfor radio frequency spectral analysis.

FIG. 9 is a diagrammatic representation illustrating one example of aUAV's flight path and points of signal data captures relative to asignal source.

FIG. 10 is a diagrammatic representation illustrating another example ofa plurality of UAVs' flight paths relative to a signal source.

FIG. 11 is a flow chart of a method for using multiple dronesconcurrently to provide a field visualization of detected radiosignal(s).

FIG. 12 is a flow chart of another method for using multiple dronesconcurrently to provide a field visualization of detected radio signals.

Like reference numerals refer to like parts throughout the several viewsof the drawings.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

As shown in the accompanying drawings, the present invention isgenerally directed to a system and method for performing radio frequency(RF) spectral analysis.

Accordingly, as shown in FIG. 1, a system 100 for RF spectral analysisgenerally comprises an unmanned aerial vehicle (UAV) 200 structured forflight and configured to detect radio signal(s) (at least one radiosignal) produced by a signal source 101 and store various parameters ofthe radio signal(s) as signal data. In at least one embodiment of thepresent invention, the UAV 200 may store the signal data in onboardmemory. In other embodiments, the UAV 200 may further be configured totransmit the signal data in real time or near real time to a receiver115 communicably connected to a processing device 111 over a network.The processing device 111 may comprise an application server having adatabase 112 thereon which may process the received signal data forvisualization. In at least one embodiment, the processed data orvisualization from the application server 111 may be remotely accessibleor viewable from a remote device 113.

The signal source(s) 101 emitting radio signal(s) may comprise a radiotower, a cellular tower, antennas, repeaters, amplifiers, or other radiosignal emitting structures or devices. The UAV 200 may maneuver tovarious locations around the signal source(s) or along the path oftravel of the various signal(s) in order to determine variouscharacteristics and parameters of the signal(s) in different points ofspace at different times. For example, the UAV may be positioned betweenor close to obstacles such as high rises, and between the antennapatterns and towers, in order to detect and map signal characteristicsfor visualization by a user. In at least some embodiments, the signalcharacteristics mapped for visualization may comprise either or both theradio signal(s) emitted by the signal source(s) 101 and/or spurious,interfering, or jamming radio signals present in proximity to the signalsource(s) 101.

In at least one embodiment, a receiver 115 may merely comprise a groundstation or computer structured and configured to receive the signal datafrom the UAV 200 that is stored thereon, whether by wired or wirelesstransmission. In a more preferred embodiment, however, the receiver 115may comprise a cellular transmission tower communicably connected tonetwork 110 via 2G, 3G, 4G, 4G LTE, 5G, WiMAX or long range WiFi, orother mobile or wireless data communication technologies known to thoseskilled in the art.

Network 110 may accordingly comprise at least the wireless datacommunication technology or platform described above. Network 110 mayfurther comprise at least two computers in communication with eachother, which may form a data network such as via LAN, WAN, Serial,Z-WAVE, ZIGBEE, RS-485, MODBUS, BACNET, the Internet. The additionalconnections may be facilitated over various wired and/or wirelessmediums or any combination thereof including interconnections by routersand/or gateways. Network 110 may comprise additional hardware componentsand/or devices appropriate for facilitating the transmission andcommunication between the various systems and devices of the presentinvention, such as those directed to integrated authentication, qualitycontrol or to improve content delivery.

Processing device 111 comprises at least one computer structured andconfigured to process the signal data from the UAV 200. Accordingly,processing device 111 comprises executable and/or interpretable computercode, or software, that allows for the visualization of the signal data.The software may comprise graphic, mathematic, or analytic software. Thesoftware may comprise commercially available software such as RF Studio,RF Explorer, MATLab, Smith Chart creation software. Of course, thesoftware may also comprise proprietary software coded in any number ofprogramming languages known to one skilled in the art, including but notlimited to C, C++, C#, Ruby, Java, Dart, Rust, Swift, PHP, Perl, HTML,XHTML, and other equivalent languages and past, present and futurevariations.

In at least one embodiment, processing device 111 may further comprisean application server, which may comprise general purpose computers,specialized computers, or other hardware components structured andconfigured to receive, process, transmit, and store information to andfrom other devices. The hardware component(s) of the application servermay comprise additional software components, such as server software forapplication(s), website(s), various network service(s), and respectivedatabases. The application server is configured with executable and/orinterpretable computer code that allows it to perform the methods andprocesses described within this application, including the processing,analysis, and/or visualization of signal data for user interpretation.The application server may implement the methodology of the usedsoftware methods described above, in conjunction with any number ofsolution stacks that allow the processing, analysis, and/orvisualization of signal data to be executed remotely. These solutionstacks may include, without limitation, ZEND Server, APACHE Server,NODE.JS, ASP, PHP, Ruby, XAMPP, LAMP, WAMP, MAMP, WISA, and others knownto those skilled in the art. In such an embodiment, the applicationserver may also comprise or be communicably connected to a database 112,the database 112 may comprise a SQL database or a text database, and mayhouse the signal data and other associated or appropriate informationthereon.

Remote device 113 may comprise a mobile device, a tablet, a computer, awearable electronic device, or any other device or combination ofcircuits structured and configured to communicate with another device,computer, or server over the network 110. The remote device 113 maycomprise application(s) and user interface(s) that allows a user tointeract with the application server described above. The user interfacemay be proprietary or may comprise a web browser, mobile browser, mobileapplication, or other application or executable code that allows forcommunication and visualization of information. In embodiments where theprocessing device 111 merely comprises a computer, the remote device 113may be unnecessary as user input and output directed to processing andvisualization of signal data may be performed entirely on the computer.

UAV 200, or drone, may comprise at least a flight body 210, and may alsocomprise various components including processor 201, memory 202, flightmodule 203, geolocation module 204, signal detection module 205, andcommunications module 206.

The flight body 210 may comprise various bodies of rotary drones,fixed-wing drones, or other known structures and appropriateconfigurations appropriate for remote controlled or preprogrammedflight. Flight body 210 may comprise commercially available droneshaving flight bodies such as or similar to KMel quadrotors, Amazon'soctacopter, Parrot AR Drone, AV Puma, and other commercially availabledrones. Flight body 210 may also comprise proprietary drones createdand/or configured with appropriate flight components such as a hull, apower source, wings and/or at least one actuated propeller. The hull maycomprise any number of materials appropriate for flight; however,lightweight and durable materials such as carbon fiber may be used in apreferred embodiment. The power source may comprise at least one batterycoupled to at least one actuator or motor. In other embodiments, thepower source may comprise gas or other fuel powered engines and/ormotors. For the present invention, a rotary drone is preferable due toits ability to hover and easily maneuver in any direction, so as toappropriately capture radio signal(s) at various points in space inbetween various objects.

The processor 201 and memory 202 are structured to allow the variousmodules to function and communicate with one another. Processor 201 maycomprise a general purpose CPU, a microprocessor, a microcontroller, orother combinations of circuits intended for bit-wise operations. Memory202 may comprise volatile or non-volatile memory, including but notlimited to RAM, ROM, flash memory, and other equivalent storage known tothose skilled in the art. In at least one embodiment, the variousmodules on the UAV may share a common processor 201 and/or memory 202for the various operations and functions described in additional detailbelow. In other embodiments, the modules recited below may furthercomprise dedicated processor(s) or memory of their own.

Flight module 203 is configured to receive programmed flightinstructions and relay the instructions to the flight body 210, in orderto facilitate unmanned flight of the UAV 200. As such, flight module 203may comprise at least one flight controller communicably connected to apower source and appropriate components of the flight body 210 necessaryor desirable for flight, including but not limited to motors, engines,gyroscopes, accelerometers, magnetometers, and appropriate sensors. In apreferred embodiment, the flight controller is configured to transmit acontrol signal to at least one actuated propeller in order to facilitatethe unmanned flight of the UAV 200. The control signal may compriseflight instructions, such as power adjustments and directionality to theactuated propeller(s) or combinations thereof. In at least oneembodiment, the flight module 203 and flight controller(s) thereof maybe pre-programmed with flight instructions. In a preferred embodiment,the flight module 203 may comprise appropriate wireless receivers or becommunicably connected to the same in order to receive the controlsignal at the flight controller in real time or near real time.

Geolocation module 204 is structured and configured to determine theUAV's present location in a three dimensional Cartesian space.Geolocation module 204 may thus comprise at least one device, such as aGPS, an altimeter, an accelerometer, a magnetometer, a barometer, agyro, a compass, and/or other components appropriate for measurement ofdistance and/or determination of locational coordinates. Geolocationdata is collected on the geolocation module 204, such as to include GPScoordinates and/or other respective sensor readings. The geolocationdata may be stored on embedded memory within the geolocation moduleand/or on memory 202 as described above.

Signal detection module 205 is configured to detect any radio signal(s)within range of the UAV and store the signal data associated with theradio signal(s). Radio signal(s) may comprise frequencies from 300 GHzto as low as 3 kHz, and may comprise various frequencies and/or bandsassociated with cellular and/or wireless networks including but notlimited to GSM, EDGE, GPRS, LTE, E-TRA, CDMA, WiMAX, HSPA, Flat IP, aswell as other wireless or cellular data standards and equivalents knownto those skilled in the art. Signal data may comprise in-phase and/orquadrature components of the radio signal(s), including amplitude,frequency, and other appropriate measurements in accordance with variousrespective analog, digital, and spread spectrum modulation schemesincluding but not limited to AM, FM, PM, QAM, SM, SSB, ASK, APSK, CPM,FSK, MFSK, MSK, OOK, PPM, PSK, QAM, SC-FDE, TCM, CSS, DSSS, FHSS, THSS,and other equivalents known to those skilled in the art. The signal datamay be stored in onboard memory on the UAV, such as at memory 202, oralternatively on embedded memory within the signal detection module 205.In a preferred embodiment, the signal data may be transmitted in realtime or near real time to a network via a communications module 206. Insuch an embodiment, the entirety of the signal data may not need to bestored on onboard UAV memory, and a memory buffer such as a circularbuffer may be sufficient.

In a preferred embodiment, signal detection module 205 comprises asoftware defined radio (SDR) and appropriate hardware components forexecuting the SDR. The hardware components comprise embedded systemsthat are capable of performing the equivalent functions of hardwareradio components including but not limited to mixers, filters,amplifiers, modulators/demodulators, detectors, convertors, and otherappropriate components. SDR may include the use of an embedded generalpurpose or specialized computer or microcontroller, receiver(s),transmitter(s), antenna(s). SDR may comprise commercially availableSDRs, SDR receivers, prebuilt SDRs, or SDR receiver kits mounted ontothe UAV 200, such as SDRstick, ADAT, Apache Labs, SunSDR, Myriad-RF,FLEX, USRP, SoftRock, and others known to those skilled in the art.

Communications module 206 is structured and configured to transmit thesignal data from the signal detection module over a network, such asnetwork 110 described above. Accordingly, communications module 206 maycomprise transceivers, antennas, and hardware logic appropriate for thetransmission of the signal data. In at least one embodiment,communications module 206 may also transmit geolocation data from thegeolocation module 204, such as GPS coordinates, altitude, compassreadings, and also noted above sensor readings.

Accordingly, some embodiments the present invention are therefore drawnto systems for radio frequency spectral analysis that comprise at leastone embodiment of the UAV 200 as described above, in combination with aprocessing device, such as processing device 111 of FIG. 1. Theprocessing device 111 is configured to process the signal data stored onthe UAV 200. In at least one embodiment, the processing device 111 maybe configured to receive the signal data over the network such asnetwork 110. The signal data may be received from the UAV 200, such asthrough its communication module 206, in real time or near real time. Ina preferred embodiment, the processing device 111 will process thesignal data for visualization of the radio signal(s) and/or signal datain three dimensional space. In order to facilitate this, sets of signaldata are taken and are tied to geolocation data such as GPS coordinatesdescribed above. For example, for each point in Cartesian space wherethe UAV 200 took a sample of radio signal(s), a set of signal data maybe stored on the UAV 200 and/or transmitted to the processing device 111and stored on a database thereon 112. Each entry of signal data may beassociated with or corresponding to a set of Cartesian coordinates or apoint in space. In another preferred embodiment, the visualization ofthe signal data associated with various points in space may also beviewable by a user in four dimensions, i.e. over a period of time.

Additional embodiments of the present invention are drawn to methods forradio frequency spectral analysis. According, and drawing attention toFIG. 3, one method for radio frequency spectral analysis may comprisefirst executing flight instructions on a UAV, as in 301, to fly in aprogrammed pattern. The flight instructions may be pre-programmed onto aflight controller of the UAV, or may be received wirelessly or remotelyin real time or near real time. The flight instructions may be based onconditional logic of the sensors of the UAV, such as the signal detectmodule. For example, the UAV may be programmed to automatically seekand/or track a pre-programmed signal pattern. In some embodiments, theUAV may be programmed to trace the path of a traveling signal and adjustflight instructions accordingly to follow the path, while compensatingand rerouting the flight path to avoid any physical obstacles based ononboard or received sensor readings.

Next, radio signal(s) are detected within range of the UAV, as in 302.Radio signals may comprise signals of various frequencies and/or bandsassociated with cellular and/or wireless networks described above. Thesignal data associated with the radio signal(s) are stored on the UAV,as in 303. Signal data may comprise in-phase and/or quadraturecomponents of any signals detected, including amplitude, frequency, andother appropriate measurements or metrics.

The signal data is transmitted from the UAV over a network, as in 351.The network may comprise the Internet in a preferred embodiment, but mayalso comprise any other LAN, WAN, wireless or partially wired networks.The signal data is received at a processing device over the network, asin 352. In a preferred embodiment, the processing device comprises anapplication server structured to process the signal data forvisualization. Of course, the processing device may merely comprise ageneral purpose or specialized computer for processing the signal data,which may be received via a physical or local wireless connection suchas USB, WiFi, Bluetooth or other NFC, or other data connection methods.

The signal data is processed for visualization on the processing device,as in 353. Commercially available or proprietary software as describedabove may be utilized for processing the signal data for visualization.The signal data may accordingly be visualized by a user in threedimensional space. Raw data may also be displayed in accordance withvarious points in space. In at least one embodiment, the user may beable to view raw data and/or the visualization of the signal in spaceover time.

FIG. 4 illustrates another method of the present invention includingsteps 301 to 303 as described above. In addition, the method illustratedfurther comprises comparing parameters of the signal data associatedwith the radio signal(s) with predetermined parameters stored on the UAVin order to determine a match, as in 401. As described above, this stepinvolves the use of conditional logic based on readings received fromthe sensors on the UAV such as through the signal detection moduleand/or geolocation module. For example, the UAV may be programmed toautomatically seek and/or track a pre-programmed signal pattern. If nomatch is found, the UAV may continue on a preprogrammed path or apseudo-random path of flight to search for the pre-programmed signalpattern.

Next, additional flight instructions are executed on the UAV, as in 402,to move to a new location. The UAV may then detect radio signal(s)within range of the UAV at the new location, as in 403. After detectionat the new location, the parameters may be compared again to determine amatch, as in 401. The steps of 401 to 403 may be repeated until theradio signals having the predetermined parameters are found.

FIG. 5 illustrates another method of the present invention includingsteps 301 to 303 as described above. In addition, the path of travel ofthe radio signal(s) may be traced, as in 501, from the respectivesource(s) to a predetermined location. This tracing may be performed bythe UAV by continuously detecting radio signal(s) from the respectivesource(s), as in 502. In accordance with the detection of the radiosignal(s), the UAV may execute flight instructions to follow the path(s)of the radio signal(s) as in 503. The UAV may further be pre-programmedto avoid any physical obstacles based on onboard or received sensorreadings during the tracing process. In some embodiments, the steps ofFIG. 4 steps 401 to 403 may be combined with the steps of 501 to 503,such as to first search out for a radio signal source having aparticular parameters, then following the path of the signal source. Forexample, a unique cellular signal such as one associated with a cellulardevice may be first sought out, then the UAV may be pre-programmed tofollow the cellular device such as to keep the matched signal withinrange.

In order to facilitate the efficient and effective detection ofparticular radio frequency signal(s), a frequency pre-selector such asshown in FIG. 6 may be utilized in additional embodiments of the presentinvention. Because of the limited processing capacities of the UAV'sonboard software defined radios (SDRs), effective processing can beenhanced by limiting the input spectrum of the radio frequencysignal(s). In other words, processing overhead may be avoided.Additionally, because cellular uplink bands have no filters, the abilitythe preselect a specific band will filter out all extraneous frequenciesand signals, thus reducing artifacts, in addition to improving dynamicrange. Accordingly, a plurality of frequencies 610, such as 611-616 ofthe radio frequency spectrum may be keyed to specific filters such as651 to 656 selectable by a switch 620. Upon selecting the desired filter651 to 656, the plurality of radio frequencies 610, or input spectrumwill be selectively filtered such as to output only the desiredfrequency, frequency range or frequency band.

FIG. 7 illustrates a schematic representation of a system 700 forpre-selecting a frequency band for radio frequency spectral analysis.Accordingly, system 700 may comprise a first receiver or signal receiver710, a radio frequency pre-selector 750, a second or separate receiver720, a software defined radio (SDR) 730, a switch controller 740.

The signal receiver 710 is structured to receive radio signal(s) asdenoted by radio signal(s) 701. Accordingly, signal receiver 710 maycomprise an antenna and appropriate circuitry for detecting radiosignal(s) 701 and processing or converting the same into usable form,i.e. as an input signal to be transmitted to the radio frequencypre-selector 750. Signal receiver 710 may comprise any number of radioreceivers known to those skilled in the art. Signal receiver 710 mayalso comprise transceivers structured and configured to not only receiveradio signal(s) but to also transmit radio signal(s).

The radio frequency pre-selector 750 may comprise a signal input modulenot shown, a pre-selector switch 751, 751′, a plurality of filtermodules 752, and a signal output module not shown. In at least oneembodiment, the radio frequency pre-selector 750 may further comprise aninterference shielding formed in enclosing relations to the radiofrequency pre-selector and its components and modules. Separate oradditional input shield and output shield may be structured to increaseisolation of the radio frequency pre-selector from undesirable signal(s)or interference at the input and output locations.

Signal input module is communicably connected to the signal receiver 710for receiving an input signal. Signal input module may merely comprisean input amplifier 753. Input amplifier 753 may comprise a low noiseamplifier in at least one embodiment in order to compensate for signallosses. Input amplifier 753 may also comprise high gains, low gains, oradjustable gains. In at least one embodiment, the pre-selector may alsocomprise a signal output module not shown, which may similarly compriseat least one output amplifier which may be the same or similar to inputamplifier 753. An output amplifier may be implemented in addition to, orin place of, the input amplifier 753.

The pre-selector switch 751, 751′ may comprise an input portion 751 andoutput portion 751′. The pre-selector switch 751, 751′ is controllableand is communicably connected to the signal receiver 710 to one of aplurality of filter modules 752. The pre-selector switch 751, 751′ maybe controllable via a wired or wireless connection through a processingdevice, such as a computer, an applications server, or remote device 113discussed in detail above. In other embodiments, the pre-selector switch751, 751′ may also be controllable via a software defined radio (SDR)which will be described in additional detail below.

The filter modules 752 each comprise at least one filter structured topass through a predefined frequency band while filtering out otherfrequency bands. Accordingly, at least one filter may comprise low-passfilters, high-pass filters, band-pass filters, band-stop filters, notchfilters, comb filters, and other appropriate filters known to thoseskilled in the art. In a preferred embodiment, at least one surfaceacoustic wave filters may be used. In other embodiments, a plurality ofsurface acoustic wave filters may be used, such as three sequentialsurface acoustic wave filters of the same band.

The software defined radio (SDR) 730 may include embedded computer,chip, or microcontroller equivalents of radio components including butnot limited to mixers, filters, amplifiers, modulators/demodulators, andother components as described above, such as at signal detection module205. The SDR may comprise a switch controller 740 for controlling thepre-selector switch 751, 751′ of the radio frequency pre-selector 750.Switch controller 740 may comprise a microcontroller or any combinationof circuits for processing input instructions and an output controlsignal. In a preferred embodiment, the switch controller 740 isconfigured to automatically switch the pre-selector switch 751, 751′ toone of the plurality of filter modules 752 that correspond to thedownlink band of a detected radio signal. In at least one embodiment,the SDR comprises and/or utilizes a separate receiver, such as receiver720, for detecting frequency band of a radio signal, in order to reduceinterference to the radio frequency pre-selector 750.

At least one other embodiment of the present invention is furtherdirected to a method for pre-selecting a frequency band for radiofrequency spectral analysis. Accordingly, radio signal(s) is/aredetected using a software defined radio, as in 801, in order to create adetected signal. The software defined radio may comprise an internalreceiver, or may detect a signal via a connected receiver such as asecond or separate receiver 720 described above.

Next, the frequency band of the detected signal is determined, as in802, on the software defined radio. In at least one embodiment, thesoftware defined radio is in communications with a radio frequencypre-selector. Based on the frequency band of the detected signal, theradio frequency pre-selector is switched, as in 803, to one of aplurality of filter modules that corresponds with the frequency band ofthe detected signal in order to connect a receiver with a selectedfilter module. The receiver in this step may comprise a first receiveror signal receiver such as 710 described above. In at least oneembodiment, the radio frequency pre-selector performs the switchingautomatically to a filter module that corresponds with the frequencyband of a detected signal. The filter module may comprise a plurality ofsurface acoustic wave filters of the same band, such as three sequentialsurface acoustic wave filters of the same band as described above.

The radio signal(s) is/are also received at the receiver, in order tocreate an input signal as in 804. The input signal is subsequentlyfiltered with the selected filter module, as in 805. In at least oneembodiment, the radio signal is detected using a first receiver on asoftware defined radio or in connection with a first receiver, while theradio frequency pre-selector is connected to a second receiver forreceiving the radio signal(s) separately, which produces the inputsignal to be filtered. Such an embodiment allows the SDR to listen whileit transmits using separate processes and components so that there is noor reduced interference. The detection of the SDR may be limited andcustomized, such as by additionally and expressly filtering out unwantedbands. The SDR may also comprise a high speed switch to more effectivelyswitch to a matching system, and may comprise additional low or highpower amplifiers to compensate for losses due to the filters.

Other embodiments of the present invention are directed to methods forusing multiple UAVs concurrently in order to provide a three dimensionalvisualization or representation of field radio signal(s) andcharacteristics. For example, it may be desirable to measure the fieldcharacteristics of a signal source such as a cellular tower radiallyfrom various points in space. Accordingly, and as illustrated in FIG. 9,a signal source 901 may comprise a radio or cellular tower, and a droneor UAV is configured to traverse a flight path circumferentially aroundthe signal source 901 in order to capture signal data of radio signal(s)emanating from the signal source 901. The resulting amplitude andfrequency of the radio signal(s) may then be plotted for two-dimensionalor three-dimensional visualization, and may further be visualized overtime. As illustrated in FIG. 10, a plurality of drones or UAVs may bedeployed concurrently in order to map a larger field, map a field inhigher resolution, i.e. by using more field capture points, or both.

As illustrated in FIG. 11, a method for radio frequency spectralanalysis may comprise executing flight instructions on a first UAV, asin 1101, to fly in a first flight pattern relative to a signal source.The first flight pattern may comprise circumnavigating the signal sourceat a first range. The first range is equivalent to the distance betweenthe first UAV and the signal source as it circumnavigates the signalsource. In other words, the first UAV may be programmed to flycircumferentially around the signal source at a predetermined distanceor first range that may be set or modified on the first UAV through itsflight module 203 and/or processor 201. In at least one embodiment, afirst range of 1 feet to 10 feet may be used. The first UAV may beconfigured through its flight module to automatically or partiallyautomatically adjust its flight trajectory to maintain the relativefirst range or distance between the first UAV and the signal source.

Radio signals emanating from the signal source are detected, as in 1102,on the first UAV. This may be performed via the UAV's signal detectionmodule 205 as described above. Desired frequency bands may be captured,including but not limited to LTE, GSM, PCS, AWS, and IMT. The signaldata may comprise GPS location, altitude, time, the particular dronethat captured the data such as an identifier or serial number, and otherappropriate or desirable information for visualizing a RF spectrumsignal data set in three dimensional space.

The signal data associated with the radio signal(s) are stored on thefirst UAV, as in 1103. This signal data may be stored in onboard memoryon the UAV, such as at memory 202, within embedded memory of the signaldetection module 205, as described above. In another embodiment, thesignal data may be transmitted in real time or near real time to anetwork via the communications module 206.

Flight instructions are similarly executed on a second UAV to fly in asecond flight pattern relative to the first flight pattern of the firstUAV, as in 1104. In at least one embodiment, the flight instructions onthe second UAV are automatically executed, upon execution of flightinstructions on the first UAV. This may be performed through an externalprocessing unit, or by way of communication between the first UAV andthe second UAV through each UAV's respective processor 201, memory 202,and communications module 206 as described above. The second flightpattern may comprise circumnavigating the signal source at a secondrange. In a preferred embodiment, the second range is two times thefirst range. For example, if the first range is a distance of 3 feetfrom the signal source, then the second range is preferably 6 feet awayfrom the signal source. In other embodiments, a multiplier of 1.1 to 3times may be used, depending on the desired resolution of the signaldata set.

The radio signals emanating from the signal source are detected, as in1105, on the second UAV. Signal data associated with the radio signal(s)are stored on the second UAV, as in 1106. In a preferred embodiment ofthe present invention, the flight instructions on the second UAV isexecuted concurrently, such that the first UAV and the second UAV eachdetect and store radio signal(s) simultaneously while flying inaccordance to each UAV's respective flight pattern.

The signal data from both the first UAV and the second UAV aretransferred to a processing device, as in 1107. The signal data isprocessed on the processing device, as in 1108, in order to create athree dimensional visualization. The processing device may comprise ageneral purpose computer or other machine as described above, anetworked computer or server structured and configured to process thesignal data for visualization, i.e. having at least a processor andmemory, as well as software configured for mapping the signal data set.In at least one embodiment of the present invention, a three dimensionalvisualization may be produced in the form of a Smith Chart.

As illustrated in FIG. 12, another method for radio frequency spectralanalysis may comprise executing initial flight instructions on a firstUAV to fly to a first starting position at a first range relative to asignal source, as in 1201. The first starting position may bepredetermined and inputted via x, y, and z coordinates on the Cartesianplane, via input of GPS coordinates and altitude, or via proximitysensors on the UAV relative to the target. The first range may bepreprogrammed into directly or inputted into the UAV remotely.

Initial flight instructions are also executed on a second UAV to fly toa second starting position at a second range relative to the signalsource, the second range being dynamically calculated based on the firstrange, as in 1202. In at least one embodiment, the second range isdynamically calculated to be two times the first range. This may beperformed by wireless communication between the first UAV and the secondUAV as described above. For example, after receiving the first range onthe first UAV either by direct programmable input or by remote input,the first UAV may then communicate to the second UAV the first range,and the second UAV may be configured to automatically calculate thesecond range based on onboard programmable logic. In another embodiment,the first UAV may calculate the second range for the second UAV. In yetanother embodiment, an external processing device, ground station, orremote device as describe above may communicate the first range to thefirst UAV and the second range to the second UAV, based on a user'sinput of the first range.

Initial flight instructions may further be executed on a third UAV tofly to a third starting position at a third range relative to the signalsource, the third range being dynamically calculated based on the secondrange, as in 1203. This process may occur similar to the determinationof the second range as described above. That is, the third range may bedetermined by the first and/or second range(s) from the first and/orsecond UAV(s), or may be directly calculated and processed by anexternal processing device.

Respective first, second, and third (if applicable) flight instructionsmay be executed, as in 1204, on the first, second, and third UAVs, whenthe first, second, and third UAVs are in their respective first, second,and third starting positions. This allows the first, second, and third,or plurality of UAVs to synchronize flight and radio frequency signalcapture. Accordingly, each of the first, second, and third (or pluralityof UAVs) may emit a “ready” signal upon arriving in position.Alternatively, an external processing device may record real-time ornear real-time GPS coordinates from each of the respective UAVs as theymove in position, and may be programmed to initiate the flight sequenceon each of the UAVs simultaneously when all UAVs are in their respectivestarting positions.

The radio signal(s) are detected, as in 1205, on each of the first,second, and third UAVs. This process may occur for each of therespective first, second, and third UAVs as described above. Signaldetection may be simultaneous with flight, or the UAV may be configuredto stop and hover at select points or at a certain time interval inorder to detect the radio frequency signal(s) from a fixed point. Thesignal data associated with the radio signal(s) are stored, as in 1206,on the first, second, and third UAVs. This process is explained above,whereby the signal data may be stored on internal memory or may betransmitted to an external device over a wireless networks, or both.

The signal data on each of the first, second, and third UAVs may then betransferred to a processing device, as in 1207. The signal data isprocessed on the processing device in order to create a three dimensionvisualization, as in 1208. A Smith Chart, or other 3D or 2Dvisualization may be created based on the datasets detected and storedon the UAVs.

In other embodiments, four or more UAVs may be utilized in order toincrease the range of the radio frequency signal capture and/or toincrease the resolution of the captured field, i.e. more capture pointsand data sets for mapping a higher resolution visualization field.

Any of the above methods may be completed in sequential order in atleast one embodiment, though they may be completed in any other order.In at least one embodiment, the above methods may be exclusivelyperformed, but in other embodiments, one or more steps of the methods asdescribed may be skipped.

Since many modifications, variations and changes in detail can be madeto the described preferred embodiment of the invention, it is intendedthat all matters in the foregoing description and shown in theaccompanying drawings be interpreted as illustrative and not in alimiting sense. Thus, the scope of the invention should be determined bythe appended claims and their legal equivalents.

What is claimed is:
 1. A method for radio frequency spectral analysiscomprising: providing at least a first UAV and a second UAV, the firstUAV and second UAV each including at least a signal detection module anda plurality of filters, flying the first UAV in a first flight patternrelative to a signal source, utilizing the signal detection module onthe first UAV to detect radio signal(s) emanating from the signalsource, flying a second UAV in a second flight pattern relative to thefirst flight pattern of the first UAV, utilizing the signal detectionmodule on the second UAV to detect radio signal(s) emanating from thesignal source, and selecting at least one of the plurality of filters inorder to selectively filter the detected radio signal(s), the selectedfilter at least partially corresponding to a downlink band of thedetected radio signal(s).
 2. The method as recited in claim 1 whereinflight instructions on the first and second UAV are executedconcurrently, such that the first UAV and the second UAV each detect andstore radio signal(s) simultaneously while flying in accordance to eachUAV's respective flight pattern.
 3. The method as recited in claim 1further comprising automatically executing flight instructions on thesecond UAV, upon execution of flight instructions on the first UAV. 4.The method as recited in claim 1 wherein the first flight patterncomprises circumnavigating the signal source at a first range.
 5. Themethod as recited in claim 4 wherein the second flight pattern comprisescircumnavigating the signal source at a second range.
 6. The method asrecited in claim 5 wherein the second range is two times the firstrange.
 7. The method as recited in claim 6 further comprisingcalculating, automatically on a processing unit, the second range of thesecond flight pattern to be two times the first range of the firstflight pattern.
 8. The method as recited in claim 7 further comprising:providing at least a third UAV, the third UAV including at least asignal detection module, flying the third UAV in a third flight patternrelative to the second flight pattern of the second UAV, and utilizingthe signal detection module on the third UAV to detect radio signal(s)emanating from the signal source.
 9. The method as recited in claim 8wherein the third flight pattern comprises circumnavigating the signalsource at a third range.
 10. The method as recited in claim 9 furthercomprising calculating, automatically on a processing unit, the thirdrange of the third flight pattern to be two times the second range ofthe second flight pattern.
 11. The method as recited in claim 1 furthercomprising: transmitting the signal data from the first UAV and thesecond UAV over a network, receiving the signal data at a processingdevice over the network, and processing the signal data forvisualization on the processing device.
 12. The method as recited inclaim 11 wherein the transmitting, receiving, and processing steps occurin real time concurrently with the radio signal(s) detection during theUAV flight.
 13. The method as recited in claim 1 wherein the signal datacomprises GPS coordinates, altitude, time, signal amplitude andfrequency.
 14. The method as recited in claim 13 further comprising:transferring the signal data from the first UAV and the second UAV to aprocessing device, and processing the signal data on the processingdevice in order to create a three dimensional visualization.